scholarly journals On distribution of a maximum of random variables

2020 ◽  
pp. 124-136
Author(s):  
Степан Алексеевич Рогонов ◽  
Илья Сергеевич Солдатенко
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Random Variables ◽  
Fuzzy Random Variables ◽  
Maximum Function ◽  
The Monte Carlo Method ◽  
Weighted Random Variables ◽  
Fuzzy Random

В работе исследуется способ идентификации методом Монте-Карло распределений нечетких случайных величин, в параметрическом задании которых присутствует функция максимума от взвешенных случайных величин. In this paper, we study a method for identifying by the Monte Carlo method distributions of fuzzy random variables, in the parametric setting of which there is a maximum function of weighted random variables.

Generation of k-wise independent random variables with small randomness

2019 ◽  
Vol 25 (3) ◽  
pp. 259-270
Author(s):  
Taku Achiha ◽  
Hiroshi Sugita ◽  
Kenta Tonohiro ◽  
Yuto Yamamoto
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Random Variables ◽  
Independent Random Variables ◽  
The Monte Carlo Method

Abstract A quick generation method of k-wise independent uniformly distributed m-bit random variables with small randomness is proposed with applications to the Monte Carlo method.

Reliability Assessment with Fuzzy Random Variables Using Interval Monte Carlo Simulation

2013 ◽  
Vol 29 (3) ◽  
pp. 208-220 ◽  
Author(s):  
Ehsan Jahani ◽  
Rafi L. Muhanna ◽  
Mohsen A. Shayanfar ◽  
Mohammad A. Barkhordari
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Reliability Assessment ◽  
Random Variables ◽  
Fuzzy Random Variables ◽  
Fuzzy Random

UGR CALCULATION BASED ON THE LUMINANCE SPATIAL-ANGULAR DISTRIBUTION

2020 ◽  
Vol 2020 (4) ◽  
pp. 25-32
Author(s):  
Viktor Zheltov ◽  
Viktor Chembaev
Keyword(s):  
Monte Carlo ◽  
Angular Distribution ◽  
Monte Carlo Method ◽  
Visual Task ◽  
New Method ◽  
Lighting System ◽  
Preliminary Assessment ◽  
System A ◽  
The Monte Carlo Method

The article has considered the calculation of the unified glare rating (UGR) based on the luminance spatial-angular distribution (LSAD). The method of local estimations of the Monte Carlo method is proposed as a method for modeling LSAD. On the basis of LSAD, it becomes possible to evaluate the quality of lighting by many criteria, including the generally accepted UGR. UGR allows preliminary assessment of the level of comfort for performing a visual task in a lighting system. A new method of "pixel-by-pixel" calculation of UGR based on LSAD is proposed.

PSHA software review based on the Monte Carlo method

2020 ◽  
pp. 14-24
Author(s):  
V.A. Mironov ◽  
S.A. Peretokin ◽  
K.V. Simonov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Seismic Hazard ◽  
Hazard Analysis ◽  
Software Review ◽  
Seismic Hazard Analysis ◽  
Probabilistic Seismic Hazard ◽  
Test Calculation ◽  
Seismic Surveys ◽  
The Monte Carlo Method

The article is a continuation of the software research to perform probabilistic seismic hazard analysis (PSHA) as one of the main stages in engineering seismic surveys. The article provides an overview of modern software for PSHA based on the Monte Carlo method, describes in detail the work of foreign programs OpenQuake Engine and EqHaz. A test calculation of seismic hazard was carried out to compare the functionality of domestic and foreign software.

Application of the Monte Carlo Method for the Prediction of Behavior of Peptides

2019 ◽  
Vol 20 (12) ◽  
pp. 1151-1157 ◽  
Author(s):  
Alla P. Toropova ◽  
Andrey A. Toropov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Natural Sciences ◽  
Monte Carlo Technique ◽  
Quantitative Structure ◽  
Structure Property ◽  
The Monte Carlo Method ◽  
Modern Natural

Prediction of physicochemical and biochemical behavior of peptides is an important and attractive task of the modern natural sciences, since these substances have a key role in life processes. The Monte Carlo technique is a possible way to solve the above task. The Monte Carlo method is a tool with different applications relative to the study of peptides: (i) analysis of the 3D configurations (conformers); (ii) establishment of quantitative structure – property / activity relationships (QSPRs/QSARs); and (iii) development of databases on the biopolymers. Current ideas related to application of the Monte Carlo technique for studying peptides and biopolymers have been discussed in this review.

Modeling grain growth by the monte carlo method on isotropic grids

1999 ◽  
Vol 72 (1) ◽  
pp. 68-72
Author(s):  
M. Yu. Al’es ◽  
A. I. Varnavskii ◽  
S. P. Kopysov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Grain Growth ◽  
The Monte Carlo Method
Sign in / Sign up

Export Citation Format

Share Document